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OU Analyse: analysing at-risk students at The Open University

Kuzilek, Jakub; Hlosta, Martin; Herrmannova, Drahomira; Zdrahal, Zdenek and Wolff, Annika (2015). OU Analyse: analysing at-risk students at The Open University. Learning Analytics Review, LAK15-1 pp. 1–16.

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Abstract

The OU Analyse project aims at providing early prediction of ‘at-risk’ students based on their demographic data and their interaction with Virtual Learning Environment. Four predictive models have been constructed from legacy data using machine learning methods. In Spring 2014 the approach was piloted and evaluated on two introductory university courses with about 1500 and 3000 students, respectively. Since October 2014 the predictions have been extended to include 10+ courses of different level. The OU Analyse dashboard has been implemented, for presenting predictions and providing a course overview and a view of individual students.

Item Type: Journal Item
Copyright Holders: 2015 The Authors
ISSN: 2057-7494
Extra Information: This paper was presented on Wednesday 18th March 2015 in the Students At Risk session and on Thursday 19th March 2015 in the Technology Showcase session of the 5th International Learning Analytics and Knowledge (LAK) Conference: Scaling Up: Big Data to Big Impact, held at Poughkeepsie, New York (USA)
Keywords: student data; distance learning; predictive models; machine learning; information visualisation
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 42529
Depositing User: Adam Jelley
Date Deposited: 16 Apr 2015 08:56
Last Modified: 03 Jun 2017 07:20
URI: http://oro.open.ac.uk/id/eprint/42529
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